Arrayed platforms or arrays typically consist of an arrangement of two or more detectors in one or more dimensions. The detectors of such arrays output data that may be monitored to observe various conditions of interest. In particular, arrayed platforms with a plethora of detectors may be useful in simultaneously monitoring a wide range of conditions by providing many different detectors and/or by utilizing numerous identical detectors for redundant measurements. However, errors still occur when characterizing data that is output from an array.
Most arrayed platforms suffer from background noise and other interferences that distort or obscure the output data resulting in erroneous measurements. This is particularly the case where the intensity of the output from each detector is close to or below the background noise threshold.
One type of arrayed platform are microarrays which typically comprise of a plurality of detectors (target probes) to which biological matter, such as a sample of genetic material (e.g., oligonucleotides, peptides, cDNA, proteins, etc.) may hybridize in some fashion to complimentary material. The genetic material used with typical microarray experiments is often labeled using fluorescence, chemiluminescence, bioluminescence, photoluminescence, or some other spectral emitter. The presence of a spectral emitter at a detector probe (also referred to herein as an object of interest) suggests that hybridization has taken place, and therefore, that the sample includes genetic material corresponding to the detector. However, the background noise on microarrays, label signals associated with non-specific hybridization, poor resolution, and protocol variations, among other things, often distort the spectral output and result in false negatives where an expressed hybridization signal is not detected, and false positives, where noise, platform defects, or other signals (such as non-specific hybridization) are incorrectly determined to be signals associated with hybridization.
The spectral intensity generated by a microarray is detected using a scanner (e.g., laser scanner, CCD array) or other detection device such as those sold by Axon, Affymetrix, Agilent and others. The detected spatial intensity is saved as a pixellated or raster output pattern data file (referred to herein as an “output pattern”). Typically, these images are saved in standard formats such as .jpg, .tif, gif, etc. and may be analyzed using a variety of analysis programs. The output patterns comprise an array of contiguous pixels that include both the pixellated intensity provided by the detectors on the array as well as other portions of the array within the total scan area of the scanner.
The total intensity emitted by an object of interest (i.e., a detector) within an output pattern is commonly referred to as a “feature” or “spot”. One or more features or spots may correspond to a specific gene that is being detected or analyzed. This identification may occur by parameterizing the spots, using spot size, spacing, layout, packaging, distortion boundaries, etc.
Traditional microarray characterization techniques analyze pixels associated with objects of interest, as well as pixels associated with background noise on the microarray. However, such techniques are imprecise and require the analysis of large amounts of data that is not germane to the microarray experiment. In addition, while some techniques attempt to extract relevant information from an output pattern, conventional systems often exclude pixels associated with an object of interest and/or include pixels associated with background results, resulting in inaccurate and imprecise characterization (especially with regard to microarrays used for weakly expressed gene detection and gene quantitation). The imprecision in results becomes worse for situations where (i) images are very noisy due to instrument, coating, linker chemistry, or platform substrate noise; (ii) images are noisy due to biological or assay noise; (iii) the sample applied to the microarray is inadequately labeled due to poor labeling efficacy; (iv) photo bleaching effects; (v) imprecise and variations in spotting; (vi) labels or dyes bleed through in images where multiple dye scanning are used in connection with energy transfer dyes; and (vii) the output patterns often do not have sufficient spatial resolution to characterize each object of interest on an array.
Conventional techniques for spot extraction utilized in hybridization images (microarrays, biochips and protein arrays), include rectilinear scanning on regular grids and the use of extraction masks. Rectilinear scanning refers to a pixellated spot represented in Cartesian (x, y) coordinate space. With this arrangement, the spot, covering m×n pixels, is either traversed in x-direction, row-by-row for the m-rows, or it is traversed in the y-direction for all the n-columns. With extraction masks, a square, circular, elliptical or polygonal mask is pre-designed as an extraction template. A “set-intersection” with the pre-configured mask is then performed to extract all the pixels that are contained within the mask boundary. The mask application may be preceded by an additional spot registration step that entails sliding the mask around the centroid of the segmented object to a position that minimizes the number of segmented pixels that are outside the mask boundary. Alternatively, the segmented object may be translated in a rectilinear or diagonal direction to increase precision. While rectilinear scanning and extraction masks provided an advantage over some extraction techniques, there remains a need for an improved system with increased precision that is adaptable to extraction non-standard spot sizes. In addition, there remains a need for an array analysis system that can provide enhanced spatial resolution over output patterns generated by a scanning/detection device.
Notwithstanding the above, arrayed platforms remain a useful and promising technique for simultaneously detecting multiple conditions of interest. Greater adoption of arrays would occur if there was a system and method for characterizing output patterns that was robust and repeatable. Accordingly, it will be appreciated that there remains a need for an improved system for extracting information relating to an object of interest within an array output pattern and for enhancing the resolution of an array output pattern. It is to these and other ends that aspects of the present invention are primarily directed.